One of the main ways of controlling accesses and developing security in cybernetics in order to protect information is recognizing and confirming individuals’ identity. Compared with other biometric methods, recognizing people through their voices is economical since it needs no special expensive equipment. Classifier, as one main part of speaker recognition system, has an important role in improving its function. Extracting speech features is one of the most important topics in the field of recognizing and identifying a speaker. The main purpose of extracting features is removing unnecessary information from speech signal and changing the speech signal into a format which makes classes separation easy in pattern recognition phase. However, all extracted features are not useful or effective. Nowadays, different methods are used for speaker recognition. In this article, we have explain two methods of speaker recognition method based on modeling methods and speaker recognition method based on feature selection. We also review the conclusion of implementing these methods.